Accurate modeling of cation–π interactions in enzymes: a case study on the CDPCho:phosphocholine cytidylyltransferase complex
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Cation–π interactions are functionally relevant, strong secondary interactions that play versatile roles in a variety of chemical and biological systems. Therefore, it is very important to be able to describe accurately and reliably these interactions. In this study, we propose a methodology for the accurate modeling of cation–π interactions in proteins using QM/MM calculations. We developed a methodology for computing the many-body interaction energy terms and tested the effect of various factors on the accuracy of the binding energy. We found that once well-equilibrated structures were reached in the MD simulations, very similar results can be obtained for the various snapshots taken from the trajectory. The calculated interaction energies were only slightly influenced by electrostatic embedding of the point charges in the QM/MM calculations and by QM/MM geometry optimization. The calculated molecular mechanics interaction energies were off by 50 % for cation–π interactions. Instead, we suggest the calibration of force fields based on fragment-based QM calculations on geometries obtained from MD simulations to yield reliable binding energies at reduced computational cost.
KeywordsCation–π interaction Energy decomposition CDPCho:phosphocholine cytidylyltransferase
The authors thank Dr. Goedele Roos (ULB, Belgium), Gergely N. Nagy, and Dr. Andras T. Rokob (MTA TTK, Hungary) for careful reading of the manuscript and helpful discussions. We are grateful for the support of the New Széchenyi Plan TAMOP-4.2.2/B-10/1-2010-0009 and for the financial support of OTKA Grant No. 108721. J.O. acknowledges receipt of a Bolyai János Research Fellowship. A.L. acknowledges the financial support of Richter Gedeon Talentum Foundation.
- 5.Luhmer M, Bartik K, Dejaegere A, Bovy P, Reisse J (1994) The importance of quadrupolar interactions in molecular recognition processes involving a phenyl group. Bull Soc Chim Fr 131:603–606Google Scholar
- 19.Zhao Y, Truhlar DG (2008) The m06 suite of density functionals for main group thermochemistry, thermochemical kinetics, noncovalent interactions, excited states, and transition elements: two new functionals and systematic testing of four m06-class functionals and 12 other functionals. Theor Chem Acc 120:215–241CrossRefGoogle Scholar
- 24.Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE, Robb MA, Cheeseman JR, Scalmani G, Barone V, Mennucci B, Petersson GA et al (2009) Gaussian 09. Revision A.1 edn. Gaussian, Inc., Wallingford, CTGoogle Scholar
- 28.Nagy GN, Marton L, Krámos B, Oláh J, Révész Á, Vékey K, Delsuc F, Hunyadi-Gulyás É, Medzihradszky KF, Lavigne M, Vial H, Cerdan R, Vértessy BG (2013) Evolutionary and mechanistic insights into substrate and product accommodation of ctp: phosphocholine cytidylyltransferase from Plasmodium falciparum. FEBS J 280:3132–3148CrossRefGoogle Scholar
- 34.Brooks BR, Brooks CL III, Mackerell AD Jr, Nilsson L, Petrella RJ, Roux B, Won Y, Archontis G, Bartels C, Boresch S, Caflisch A, Caves L, Cui Q, Dinner AR, Feig M, Fischer S, Gao J, Hodoscek M, Im W, Kuczera K, Lazaridis T, Ma J, Ovchinnikov V, Paci E, Pastor RW, Post CB, Pu JZ, Schaefer M, Tidor B, Venable RM, Woodcock HL, Wu X, Yang W, York DM, Karplus M (2009) Charmm: the biomolecular simulation program. J Comput Chem 30:1545–1614CrossRefGoogle Scholar
- 39.Tinker—home page. Tinker—software tools for molecular design. http://dasher.Wustl.Edu/tinker/. Accessed 5 Oct 2011
- 44.Glendening ED, Badenhoop JK, Reed AE, Carpenter JE, Bohmann JA, Morales CM, Weinhold F (2009) NBO 5.9. Theoretical Chemistry Institute, University of Wisconsin, Madison, WIGoogle Scholar